Understanding healthy life expectancy and the dynamics of health status prevalence Seminar
- Time:
- 16:00 - 17:00
- Date:
- 12 October 2011
- Venue:
- Building 44 Room 2103
For more information regarding this seminar, please email Professor Graham Moon at G.Moon@soton.ac.uk .
Event details
Geography and Environment seminar
This talk tries to make sense of what we might expect in terms of health in the face of continuing population ageing, drawing on research on the older populations of Thailand (with Rukchanok Karcharnubarn) and Northern England (with Chengchao Zuo). Thailand’s rapid demographic transition results in population ageing, which will accelerate in future. In 2005 Thailand’s population aged 65+ was 4.5 million. Official projections suggest a 65+ population of 9.8 million by 2025. The older population will age, because life expectancy after 65 is improving. We estimate how much life is spent in good health and poor, using healthy life expectancy. This study investigates changes in healthy life expectancy in Thailand, based on data from Surveys of the Elderly in 2002 and 2007. Life expectancy in self-rated good health and free of disability were calculated using prevalence rates (Sullivan’s method). Life expectancy beyond age 60 increased between 2002 and 2007. The proportions of life lived in self-rated poor health and with self-care disability increased while years with mobility disability decreased. We explore scenarios that project the older population of Thailand by health status. For Northern England we explore how many people will experience limiting long-term illness (LLTI) in the years to 2036, using new projections for localities combined with prevalence rates from the 2001 Census. Both the Thailand and Northern England studies could not reliably measure trends in health status prevalence rates, but we know from the work of Sanderson and Scherbov (2010) that if trends follow those in their model the picture could be quite different. The talk concludes with an illustrative “what if” scenario for Northern England using possible trends in LLTI.
Speaker information
Philip Rees , University of Leeds. School of Geography